• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집D
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• pp.771-776
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• 2001

By matching a well established fast throughflow code, with standard loss correlations, and an efficient optimization algorithm, a new design system has been developed, which optimizes inlet and exit flow-field parameters for each blade row of a multistage axial flow turbine. The compressible steady state inviscid throughflow code based on streamline curvature method is suitable for fast and accurate flow calculation and performance prediction of a multistage axial flow turbine. A general purpose hybrid constrained optimization package, iSIGHT has been used, which includes the following modules: genetic algorithm, simulated annealing, modified method of feasible directions. The design system has been demonstrated using an example of a 5-stage low pressure steam turbine for 800MW thermal power plant previously designed by HANJUNG. The comparison of computed performance of initial and optimized design shows significant improvement in the turbine efficiency.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.1022-1027
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• 2004

In this study, the shape of plate-fin type heat sink is numerically optimized to acquire the minimum pressure drop under the required temperature rise. To do this, a new sequential approximate optimization (SAO) is proposed and it is integrated with the computational fluid dynamics (CFD). In thermal/fluid systems for constrained nonlinear optimization problems, three fundamental difficulties such as high cost for function evaluations (i.e., pressure drop and thermal resistance), the absence of design sensitivity information, and the occurrence of numerical noise are confronted. To overcome these problems, the progressive quadratic response surface method (PQRSM), which is one of the sequential approximate optimization algorithms, is proposed and the heat sink is optimize by means of the PQRSM.

• 제어로봇시스템학회논문지
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• 제7권8호
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• pp.641-646
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• 2001

Eigenstructure assignment is a typical method with the capability of consideration of the time-domain specifications in designing a linear control system. In this paper, we propose a new method for eigenstructure to achieve desired eigenvectors more precisely than with the conventional method. In the proposed method, the conventional eigenstructure assignment problem is interpreted as a constrained optimization one, and it converted into an unconstrained optimization problem to deal with the problem easily. Numerical examples are presented to illustrate the proposed flexible eigenstructure assignment method.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제50권10호
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• pp.494-500
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• 2001

This paper presents the shape optimization to minimize the BEMF(Back Electro-Motive Force) harmonics of PM type synchronous generators. RSM(Response Surface Methodology) is well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. In this paper, RSM is used to find the optimal solution. The 2D-Finite Element Method is used to obtain the observer data of the BEMF and SQP(Sequential Quadratic Problem method) is used to solve the constrained nonlinear optimization problem.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.43-48
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• 2003

In this study the optimization of plate-fin type heat sink for the thermal stability is performed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained nonlinear optimization problem. The results show that when the temperature rise is less than 34.6 K, the optimal design variables are as follows; $B_{1}$ = 2.468 mm, $B_{2}$ = 1.365 mm, and t = 10.962 mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• International Journal of Automotive Technology
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• 제8권1호
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• pp.39-48
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• 2007

This paper addresses the problem of period and priority assignment in networked control systems (NCSs) using a fixed priority scheduler. The problem of assigning periods and priorities to tasks and messages is formulated as an optimization problem to allow for a systematic approach. The temporal characteristics of an NCS should be considered by defining an appropriate performance index (PI) which represents the temporal behavior of the NCS. In this study, the sum of the end-to-end response times required to process all I/Os with precedence relationships is defined as a PI. Constraints are derived from the task and message deadline requirements to guarantee schedulability. Genetic algorithms are used to solve this constrained optimization problem because the optimization formulation is discrete and nonlinear. By considering the effects of communication, an optimum set of periods and priorities can be holistically derived.

• ETRI Journal
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• 제33권3호
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• pp.299-309
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• 2011

Energy consumption is a key issue in body sensor networks (BSNs) since energy-constrained sensors monitor the vital signs of human beings in healthcare applications. In this paper, packet size optimization for BSNs has been analyzed to improve the efficiency of energy consumption. Existing studies on packet size optimization in wireless sensor networks cannot be applied to BSNs because the different operational characteristics of nodes and the channel effects of in-body and on-body propagation cannot be captured. In this paper, automatic repeat request (ARQ), forward error correction (FEC) block codes, and FEC convolutional codes have been analyzed regarding their energy efficiency. The hop-length extension technique has been applied to improve this metric with FEC block codes. The theoretical analysis and the numerical evaluations reveal that exploiting FEC schemes improves the energy efficiency, increases the optimal payload packet size, and extends the hop length for all scenarios for in-body and on-body propagation.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.407-422
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• 2004

A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제51권2호
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• pp.55-60
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• 2002

This paper presents an optimization procedure by using Response Surface Methodology(RSM) to determine design parameters for reducing cogging torque. RSM is achieved through using the experimental design method in combination with Finite Element Method and adapted to make analytical model for a complex problem considering a lot of interaction of these parameters. Sequential Quadratic Problem (SQP) method is used to solve the relsulting of constrained nonlinear optimization problem.